NOLOGIES TRADA ADAMUS CHNOLOGIES Robotic Arm Control Via EMG - - PowerPoint PPT Presentation

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NOLOGIES TRADA ADAMUS CHNOLOGIES Robotic Arm Control Via EMG - - PowerPoint PPT Presentation

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N OSTR MUS T ECH NOLOGIES TRADA ADAMUS CHNOLOGIES Robotic Arm Control Via EMG Signal U NIVERSITY OF S OUTH C AROLINA Don Groves Leader Kevin Tangen Jake Tomlinson grovesd@email.sc.edu tangenk@email.sc.edu Tomlins2@email.sc.edu Problem

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Robotic Arm Control Via EMG Signal

Don Groves – Leader grovesd@email.sc.edu UNIVERSITY OF SOUTH CAROLINA Kevin Tangen tangenk@email.sc.edu Jake Tomlinson Tomlins2@email.sc.edu

NOSTR

TRADA ADAMUS MUS TECH CHNOLOGIES NOLOGIES

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SLIDE 2

Problem Definition

  • Global need for specialized surgeons

– Third world countries – Hostile environments

  • Obstacles:

– Time – Money – Safety

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SLIDE 3

Background

  • Current robotic systems:

– Supervisory control system – Telesurgical system

  • Da Vinci surgical system

– Shared control system

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SLIDE 4
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SLIDE 5

Components

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SLIDE 6

Project Progression

  • EMG Signals
  • Programming

Languages

  • Robotic Arm Models

Research

  • Muscles
  • Data Collection
  • LabVIEW Integration

BioRadio

  • Signal Filtering
  • Signal Amplification

LabVIEW

  • LabVIEW Integration
  • BioRadio Control

AL5B

  • Differential Signal

Analysis

  • 3 Servo Motors
  • Practice Controlling

Full System

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SLIDE 7

LabVIEW Program

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SLIDE 8

LabVIEW Control Panel

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Results

Develop a VI in LabVIEW to control all components Control a single servo motor using a live EMG Incorporate three EMG channels Perform tests to assess accuracy and precision

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Data

Trial Distance from Target (cm) 1 3.00 2 1.20 3 0.40 4 2.30 5 0.80 6 0.60 7 1.10 8 0.50 9 0.20 10 0.80 Pointing Accuracy Trial Target Depth (cm) Experimental (cm) Percent Error 1 2.00 4.50 125.00 2 2.00 3.70 85.00 3 2.00 0.70 65.00 4 2.00 2.60 30.00 5 2.00 3.10 55.00 6 2.00 1.60 20.00 7 2.00 2.10 5.00 8 2.00 2.40 20.00 9 2.00 1.80 10.00 10 2.00 1.90 5.00 Depth Test Trial Target length (cm) Experimental (cm) Percent Error 1 8.00 5.50 31.25 2 8.00 2.40 70.00 3 8.00 6.00 25.00 4 8.00 8.50 6.25 5 8.00 9.30 16.25 6 8.00 6.90 13.75 7 8.00 7.60 5.00 8 8.00 7.20 10.00 9 8.00 5.80 27.50 10 8.00 8.20 2.50 Test Cut Length

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SLIDE 11

Wrist Control

  • Video
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Elbow Joint

  • Video
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SLIDE 13

Shoulder Control

  • Video
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SLIDE 14

Robotic Arm Arc Cut

  • Video
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Twitchy Cut

  • Video
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Failed Cut

  • Video
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Successful Cut

  • Video
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Straight line

  • Video
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Robotic Arm 2-Planes

  • Video
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Robotic Arm Back and Forth

  • Video
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Obstacles

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Conclusion

Obtained and processed EMG signal Isolated robotic arm to 3 DOF Operated 3 motors with 3 corresponding pairs of opposing muscle groups Performed cutting motion of specified length and depth using the BioRadio/LabVIEW/AL5B system

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Acknowledgements

  • We would like to thank:

– Our advisor – Dr. Abdel Bayoumi, USC – Our sponsor – Dr. Joseph Giuffrida, CleveMed – Our thesis second readers – Dr. Francisco Gonzalez, USC; Dr. Brian Helmuth, USC – Our technical support – Russell Tomlinson, Robert

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References

  • Artemiadis, P.K., Kyriakopoulos, K.J., “EMG-based teleoperation of a robot arm in
  • planar catching movements using ARMAX model and trajectory monitoring techniques.” IEEE

Transactions on Robotics and Automation (2006): 3244-49. Print.

  • Bonsor, Kevin, “How Robotic Surgery Will Work.” Discovery Company.
  • http://science.howstuffworks.com/robotic-surgery4.htm accessed: 04/05/2011
  • Farry, K.A., Walker, I.D., and Baraniuk, R.G., “Myoelectric teleoperation of a complex
  • robotic hand.” IEEE Transactions on Robotics and Automation, 12.5 (1996).
  • Han, J., Song, W., Kim, J., Bang, W., Lee, H., and Bien, Z., “New EMG Pattern
  • Recognition based on Soft Computing Techniques and Its Application to Control
  • f a Rehabilitation Robotic Arm.” KAIST (2000): 890-97. Print.
  • Hidalgo, M., Tene, G., and Sánchez, A., “Fuzzy Control of a Robotic Arm using EMG
  • Signals.” IEEE, (2005).
  • Kiguchi, K., Tanaka, T., and Fukuda, T., "Neuro-Fuzzy Control of a Robotic Exoskeleton
  • With EMG Signals." IEEE Transactions on Fuzzy Systems 12.4 (2004): 481-90. Print.